Comprehensive analysis of aquaculture research trends focusing on Internet of Things, machine learning, water quality monitoring, and cybersecurity over two decades using bibliometric data

• A comprehensive bibliometric review bridging ML, IoT, water quality, and cybersecurity in smart aquaculture. • A reproducible synthesis of 2,228 publications (2000–2025) from major databases ensures methodological rigor. • Global research trends analyzed through publication and collaboration networks highlighting key contributors. • Thematic evolution revealed via keyword co-occurrence and clustering, showing emerging smart aquaculture hotspots. Smart aquaculture that integrates Secure Internet of Things (IoT) and Machine Learning (ML) is vital for sustainable food production but remains fragmented and insufficiently structured. There is a lack of bibliometric analysis limiting a clear understanding of current research trends and technical challenges. The proposed research presents a comprehensive bibliometric analysis of the field from 2000 to 2025, based on a triangulated dataset of 2228 publications retrieved from Scopus, Web of Science(WoS), and Institute of Electrical and Electronics Engineers(IEEE)Xplore. Records were systematically collected, deduplicated, and analyzed using Bibliometrix and VOSviewer, with sensitivity checks confirming database robustness. Results reveal exponential growth of research output after 2020, with China and India emerging as leading contributors, followed by the United States and several European nations. The analysis highlights English language publications are dominant. Additionally, top contributing institutions, and strong international collaborations, alongside thematic hotspots such as Deep Learning (DL) for disease prediction, real time water quality forecasting, blockchain enabled traceability, and secure IoT frameworks are discussed. Novel dimensions are also captured, including equity in geographic and species research, limited attention to data governance and privacy, and early signals of sustainability concerns such as energy efficiency and lifecycle assessment. These findings provide strategic insights for researchers, industry, and policy makers, while underscoring that future progress in smart aquaculture will depend as much on governance and sustainability as on technological innovation.